{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = pd.Series(np.random.randn(10),\n",
    "              index = np.arange(0,50,5))\n",
    "s.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-1.492145</td>\n",
       "      <td>-0.192991</td>\n",
       "      <td>0.507393</td>\n",
       "      <td>0.456367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>-2.464788</td>\n",
       "      <td>-1.295381</td>\n",
       "      <td>0.574900</td>\n",
       "      <td>1.661855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>-1.191266</td>\n",
       "      <td>-1.587712</td>\n",
       "      <td>0.449696</td>\n",
       "      <td>0.470602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>-1.559158</td>\n",
       "      <td>-0.710578</td>\n",
       "      <td>-0.418082</td>\n",
       "      <td>-0.854800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.502816</td>\n",
       "      <td>0.464582</td>\n",
       "      <td>-2.238241</td>\n",
       "      <td>-0.541974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>0.275768</td>\n",
       "      <td>0.760057</td>\n",
       "      <td>-2.473463</td>\n",
       "      <td>-0.221367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>-1.333971</td>\n",
       "      <td>0.591649</td>\n",
       "      <td>-2.648625</td>\n",
       "      <td>0.203866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>0.179241</td>\n",
       "      <td>0.939359</td>\n",
       "      <td>-1.251183</td>\n",
       "      <td>2.460328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>-0.150354</td>\n",
       "      <td>2.355146</td>\n",
       "      <td>-2.206533</td>\n",
       "      <td>2.682408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>0.076939</td>\n",
       "      <td>1.724468</td>\n",
       "      <td>-3.338535</td>\n",
       "      <td>2.923226</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           a         b         c         d\n",
       "0  -1.492145 -0.192991  0.507393  0.456367\n",
       "10 -2.464788 -1.295381  0.574900  1.661855\n",
       "20 -1.191266 -1.587712  0.449696  0.470602\n",
       "30 -1.559158 -0.710578 -0.418082 -0.854800\n",
       "40  0.502816  0.464582 -2.238241 -0.541974\n",
       "50  0.275768  0.760057 -2.473463 -0.221367\n",
       "60 -1.333971  0.591649 -2.648625  0.203866\n",
       "70  0.179241  0.939359 -1.251183  2.460328\n",
       "80 -0.150354  2.355146 -2.206533  2.682408\n",
       "90  0.076939  1.724468 -3.338535  2.923226"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.random.randn(10,4).cumsum(0),\n",
    "                  index = np.arange(0,100,10),\n",
    "                  columns=['a', 'b', 'c', 'd'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2,1)\n",
    "data = pd.Series(np.random.randn(16),\n",
    "                 index=list('abcdefghijklmnop'))\n",
    "data.plot(ax=axes[0], kind='bar')\n",
    "data.plot(ax=axes[1], kind='barh')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>one</th>\n",
       "      <td>0.647020</td>\n",
       "      <td>0.817127</td>\n",
       "      <td>0.892389</td>\n",
       "      <td>0.446059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tw</th>\n",
       "      <td>0.597632</td>\n",
       "      <td>0.124273</td>\n",
       "      <td>0.232335</td>\n",
       "      <td>0.598443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>th</th>\n",
       "      <td>0.184103</td>\n",
       "      <td>0.027525</td>\n",
       "      <td>0.823474</td>\n",
       "      <td>0.916741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fo</th>\n",
       "      <td>0.312388</td>\n",
       "      <td>0.419980</td>\n",
       "      <td>0.915796</td>\n",
       "      <td>0.370672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fi</th>\n",
       "      <td>0.746603</td>\n",
       "      <td>0.536363</td>\n",
       "      <td>0.690369</td>\n",
       "      <td>0.818498</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            A         B         C         D\n",
       "one  0.647020  0.817127  0.892389  0.446059\n",
       "tw   0.597632  0.124273  0.232335  0.598443\n",
       "th   0.184103  0.027525  0.823474  0.916741\n",
       "fo   0.312388  0.419980  0.915796  0.370672\n",
       "fi   0.746603  0.536363  0.690369  0.818498"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.random.rand(6,4),\n",
    "                  index = ['one', 'tw', 'th', 'fo', 'fi', 'si'],\n",
    "                  columns=pd.Index(['A', 'B', 'C', 'D']))\n",
    "                  \n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='A', ylabel='B'>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.scatter('A', 'B')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.10"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
